How Much RAM You Need for Local AI on a R100,000 SA Budget

Running local AI well in South Africa is less about a single shopping rule and more about matching system RAM, VRAM and storage to the models you actually load. On a R100,000 budget the smart move is to spend where it removes the real bottleneck rather than maxing one number.

Quick Answer

For local AI on a R100,000 budget, fit 64GB, with 128GB worth it for serious work of system RAM and prioritise GPU VRAM, since the GPU buffer decides which models run fast. With this you can handle 30B to 70B parameter models with quantisation, plus headroom for big context windows.

Why VRAM Leads, RAM Supports

For local inference, the model ideally lives in GPU VRAM. A 12GB to 16GB card runs many 7B and 13B models at usable speeds; 24GB and up opens larger models. System RAM matters when a model spills out of VRAM or when you keep large datasets and multiple apps open. On a R100,000 budget, balance the two: enough VRAM to fit your target model, then enough RAM so the rest of the workflow never swaps to disk.

Memory speed and capacity both count. A dual-channel DDR5 kit at 6000MT/s feeds the CPU efficiently, and 64GB is the practical floor for comfortable local AI alongside a browser and editor. Going below that forces constant paging that stalls inference.

Allocating a R100,000 Local-AI Budget

At R100,000, you can afford a 24GB or larger GPU, 64GB of DDR5, and generous NVMe storage. That combination runs large quantised models and keeps big context windows responsive. Evetech stocks GPUs, DDR5 kits and NVMe drives with local warranty, so you can build a balanced AI workstation in one order.

FAQ

How much RAM do I need for local AI on a R100,000 budget?

Fit 64GB, with 128GB worth it for serious work of DDR5. That keeps the CPU side responsive while the GPU's VRAM does the heavy lifting for the models themselves.

Is system RAM or VRAM more important for local AI?

VRAM usually decides which models run fast, so it leads the budget. System RAM is the support layer that stops the rest of your workflow from swapping to disk while a model is loaded.

Do I need DDR5 or is DDR4 fine?

DDR5 is the better choice for new local-AI builds thanks to higher bandwidth, which helps when a model partly spills into system memory. A 6000MT/s dual-channel kit is a sensible target.